Method for determining the position of impacts

ABSTRACT

A method for determining the position of impacts on an object comprising two acoustic sensors, and N active areas of said object, comprises the steps of: (a) receiving two acoustic signals S 1 (t) and S 2 (t); (b) calculating a sample signature function SIG S (ω)=S 1 (ω)−S 2 (ω)*, where S 1 (ω) and S 2 (ω) are the respective Fourier transforms of S 1 (t) and S 2 (t), (c) comparing SIG S (ω) with N predetermined reference signature functions SIG R ,(ω) corresponding to the predetermined area j for j from 1 to N; (d) determining the active area in which the impact occurred, on the basis of the comparison of step (c).

FIELD OF THE INVENTION

The present invention relates to a method for determining the position of impacts, and a device using this method.

BACKGROUND OF THE INVENTION

A known method for determining the position of impacts on an object is suggested by Patent FR 2 841 022. According to this document, the object may comprise two acoustic sensors and N predetermined active areas of said object, whereby N is an integer at least equal to 1. In order to determine the active area in which an impact occurred, acoustic signals received by the acoustic sensors are compared with N acoustic signals, recorded in a database, and each corresponding with one of the N predetermined areas. Consequently, it leads to 2N comparison calculations to complete the task, when two sensors are used.

An object of the present invention is to provide a method for determining an impact position, whose calculation velocity is improved, and which does not require a high computing power.

SUMMARY OF THE INVENTION

The invention thus proposes a method for determining the position of impacts on an object, said object comprising:

two acoustic sensors;

N predetermined active areas, whereby N is an integer at least equal to 1;

said method comprising the steps of: (a) receiving two acoustic signals S₁(t) and S₂(t) originating respectively from said acoustic sensors and generated by an impact received on said object; (b) calculating a sample signature function:

SIG _(S)(ω)=S ₁(ω)·S ₂(ω)*,

where S₁(ω) and S₂(ω) are the respective Fourier transforms of S₁(t) and S₂(t), and where * is the complex conjugate operator; (c) comparing SIG_(S)(ω) with N predetermined reference signature functions SIG_(Rj)(ω) each corresponding to a predetermined active area j, for j from 1 to N; (d) determining an active area in which the impact occurred, on the basis of the comparison of step (c).

In various embodiments of the method according to the invention, at least one of the following characteristics may be used:

-   -   each reference signature function equals:

SIG _(R) _(j) (ω)=R ₁ j(ω)·R ₂ j(ω)*

where R_(1j)(ω) and R_(2j)(ω) are Fourier transforms of acoustic signals R_(1j)(t) and r_(2j)(t) received by each of the respective acoustic sensors when an impact occurs on the predetermined area j;

-   -   step (c) comprises the calculation of a similarity estimator         α_(j) representing a function of the phase φ(COR_(j)(ω)) of         COR_(j)(ω)=SIG_(R) _(j) (ω)·SIG_(S)(ω)*;     -   step (c) comprises the calculation of a function δ_(j)(ω) for j         from 1 to N, wherein         δ_(j)(ω)=ε_(k), if φ(COR_(j)(ω)) belongs to I_(k),         where ε_(k) is a predetermined value and I_(k) a corresponding         angular interval for k from 1 to n, where n is an integer         greater than 1;     -   the values ε_(i) are not greater than 1;     -   in the method:         if |φ(COR_(j)(ω))|≦a1, then δ_(j)(ω)=ε₁,         . . .         if n is greater than 2 and a_(k-1)<|φ(COR_(j)(ω))|≦a_(k), then         δ_(j)(ω)=ε_(k), for k=2 . . . n−1,         . . .         if |φ(COR_(j)(ω))|>a_(n−1), then δ_(j)(ω)=ε_(n),         wherein a_(k) is increasing with k and ε_(k) is decreasing with         k;     -   in the method:         if Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₁), then δ_(j)(ω)=ε₁,         . . .         if n is greater than 2 and         |Im(COR_(j)(ω))|/tan(a_(k-1))>Re(COR_(j)(ω))≧Im(COR_(j)( ))|/tan(a_(k)),         then δ_(j)(ω)=ε_(k), for k=2 . . . n−1,         . . .         else, δ_(j)(ω)=ε_(n),         and wherein Re(COR_(j)(ω)) is the real part of COR_(j)(ω) and         Im(COR_(j)(ω)) is the imaginary part of COR_(j)(ω);     -   in the method:         if γ_(j)(ω)≧β_(j)(ω)/tan(a₁), then δ_(j)(ω)=ε₁=1;         . . .         if n is greater than 2 and         β_(j)(ω)/tan(a_(k-1))>γ_(j)(ω)≧β_(j)(ω)/tan(a_(k)), then         δ_(j)(ω)=ε_(k), for k=2, . . . n−1;         . . .         else, δ_(j)(ω)=ε_(n),         and wherein:         β_(j)(ω)=|1+{A_(j)(ω)/B_(j)(ω)}·{(D (ω)/C(ω)}|,         γ_(j)(ω)=signB_(j)(ω)·signC(ω)·[{A_(j)(ω)/B_(j)(ω)}−{D(ω)/C(ω)}],         signB_(j)(ω)=1 if B_(j)(ω) is positive and =−1 if B_(j)(ω) is         negative,         signC(ω)=1 if C(ω) is positive and =−1 if C(ω) is negative,         A_(j)(ω) and B_(j)(ω) are respectively the real part and the         imaginary part of each reference signature function SIG_(Rj)(ω),         C(ω) and D(ω) are respectively the real part and the imaginary         part of the complex conjugate sample signature function         SIG_(S)(ω)*;     -   ε₁=1 and ε_(n)=0;     -   n is greater than 2 and ε_(k)=cos(a_(k-1)) for k=2, . . . n−1.

α_(j) =K·∫ _(B)δ_(j)(ω)·dω,

where B is a frequency interval and K a constant;

-   -   B=[ω_(min),ω_(max)] and K is proportional to         1/(ω_(max)−ω_(min));     -   the active area j₀ in which the impact occurred is determined         such that α_(j) ₀ is the greatest similarity estimator among the         N calculated similarity estimators α_(j);     -   it is concluded that the impact occurred in the area j₀ only if         α_(j) ₀ is considered as valid in step (d);     -   α_(j) ₀ is considered as valid if α_(j) ₀ is greater than a         predetermined threshold of confidence;     -   it is concluded that there is no impact if α_(j) ₀ is not         considered as valid in step (d);     -   step (a) begins if the acoustic signals S₁(t) and S₂(t) are         above a predetermined trigger threshold;     -   the acoustic signals S₁(t) and S₂(t) in step (a) are delayed         relative to real audio signals;     -   the Fourier transform is a Fast Fourier transform.

Besides, another object of the invention is a device for determining the position of impacts on an object, by comprising:

two acoustic sensors adapted to be borne by said object for receiving acoustic signals S₁(t) and S₂(t) generated by an impact on said object;

memory means comprising N reference signature functions, corresponding to N predetermined active areas of said object, whereby N is an integer at least equal to 1;

calculation means for calculating a sample signature function

SIG _(S)(ω)=S ₁(ω)·S ₂(ω)*,

where S₁(ω) and S₂(ω) are the respective Fourier transforms of S₁(t) and S₂(t), and where * is the complex conjugate operator;

comparison means for comparing SIG_(S)(ω) with N predetermined reference signature functions SIG_(R) _(j) (ω) for j from 1 to N;

processing means for determining an active area (1 a) in which the impact occurred, on the basis of results given by said the comparison means.

In various embodiments of the device according to the invention, one may use one and/or other of the following features:

-   -   each reference signature function equals:

SIG _(R) _(j) (ω)=R ₁ j(ω)·R ₂ j(ω)*

where R_(1j)(ω) and R_(2j)(ω) are Fourier transforms of acoustic signals r_(1j)(t) and r_(2j)(t) received by each of the respective acoustic sensors when an impact occurs on the predetermined area j;

-   -   said comparison means are adapted to calculate of a similarity         estimator α_(j) representing a function of the phase         φ(COR_(j)(ω)) of COR_(j)(ω)=SIG_(R) _(j) (ω)·SIG_(S)(ω)*;     -   said comparison means are adapted to calculate a function         δ_(j)(ω) for j from 1 to N, wherein         δ_(j)(ω)=ε_(k), if φ(COR_(j)(ω)) belongs to I_(k),         where ε_(k) is a predetermined value and I_(k) a corresponding         angular interval for k from 1 to n, where n is an integer         greater than 1;     -   the values ε_(i) are not greater than 1;     -   said comparison means are adapted so that:         if |φ(COR_(j)(ω)|≦a1, then δ_(j)(ω)=ε₁,         . . .         if n is greater than 2 and a_(k-1)<|φ(COR_(j)(ω))|≦a_(k), then         δ_(j)(ω)=ε_(k), for k=2 . . . n−1,         . . .         if |φ(COR_(j)(ω))|>a_(n−1), then δ_(j)(ω)=ε_(n),         wherein a_(k) is increasing with k and ε_(k) is decreasing with         k;     -   said comparison means are adapted so that:         if Re(COR_(j)(ω)>|Im(COR_(j)(ω))|/tan(a₁), then δ_(j)(ω)=ε₁,         . . .         if n is greater than 2 and         |Im(COR_(j)(ω))|/tan(a_(k-1))>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a_(k)),         then δ_(j)(ω)=ε_(k), for k=2 . . . n−1,         . . .         else, δ_(j)(ω)=ε_(n),         and wherein Re(COR_(j)(ω)) is the real part of COR_(j)(ω) and         Im(COR_(j)(ω)) is the imaginary part of COR_(j)(ω);     -   said comparison means are adapted so that:         if γ_(j)(ω)≧β_(j)(ω)/tan(a₁), then δ_(j)(ω)=ε₁=1;         . . .         if n is greater than 2 and         β_(j)(ω)/tan(a_(k-1))>γ_(j)(ω)≧β_(j)(ω)/tan(a_(k)), then         δ_(j)(ω)=ε_(k), for k=2, . . . n−1;         . . .         else, δ_(j)(ω)=ε_(n),         and wherein:         β_(j)(ω)=|1+{A_(j)(ω)/B_(j)(ω)}·{(D(ω)/C(ω)}|,         γ_(j)(ω)=signB_(j)(ω)·signC         (ω)·[{A_(j)(ω)/B_(j)(ω)}−{D(ω)/C(ω)}],         signB_(j)(ω)=1 if B_(j)(ω) is positive and =−1 if B_(j)(ω) is         negative,         signC(ω)=1 if C(ω) is positive and =−1 if C(ω) is negative,         A_(j)(ω) and B_(j)(ω) are respectively the real part and the         imaginary part of each reference signature function SIG_(Rj)(ω),         C(ω) and D(ω) are respectively the real part and the imaginary         part of the complex conjugate sample signature function         SIG_(S)(ω)*;     -   ε₁=1 and ε_(n)=0;     -   n is greater than 2 and ε_(k)=cos(a_(k-1)), for k=2, . . . n−1;     -   said comparison means are adapted so that:

α_(j) =K·∫ _(B)δ_(j)(ω)·dω,

where B is a frequency interval and K a constant;

-   -   the processing means are adapted to determine the active area j₀         in which the impact occurred such that α_(j) ₀ is the greatest         similarity estimator among the N calculated similarity         estimators α_(j);     -   the processing means are adapted to determine that the impact         occurred in the area j₀ only if α_(j) ₀ is considered as valid;     -   the processing means are adapted to determine that α_(j) ₀ is         valid if α_(j) ₀ is greater than a predetermined threshold of         confidence;     -   the processing means are adapted to determine that there is no         impact if α_(j) ₀ is not considered as valid.

This method and this device permit to reduce the number of comparisons to N, as the sampled acoustic signals are no longer compared with each reference acoustic signal, but with a signature function for each pair of reference acoustic signals. Furthermore, the calculation of the signature functions does not require a high calculation power. Moreover, as explained below, the phase of a signature function does not depend on the excitation waveform, but only on the place in which the impact occurred. Consequently, by studying only the phase of the signature function, the active area in which the impact occurred may be determined.

BRIEF DESCRIPTION THE DRAWINGS

Other features and advantages of the invention will appear from the following description of three embodiments of the invention, given by way of non-limiting example, with regard to the appended drawings. In the drawings:

FIG. 1 is a schematic view of an example of device according to the invention;

FIG. 2 is a flow chart describing a method according to a first embodiment of the invention;

FIGS. 3A and 3B are graphics illustrating the calculation of a similarity estimator according to the first embodiment of the invention;

FIGS. 4A and 4B are graphics illustrating the calculation of a similarity estimator according to a second embodiment of the invention; and

FIG. 5 is a flow chart describing a method according to a third embodiment of the invention.

MORE DETAILED DESCRIPTION

As illustrated by FIG. 1, the present invention may be carried out for instance by a device comprising an object 1 and two acoustic sensors SENS1 and SENS2 borne by said object 1.

This object 1 may be for instance a table, a door, a wall, a screen or other things, and is made for instance of wood, metal, cement, glass or other materials. The acoustic sensors SENS1 and SENS2 may be for example piezoelectric sensors or any other sensor able to sample a vibration transmitted in the object, such as capacitive sensors, magnetostrictive sensors, electromagnetic sensors, acoustic velocimeters, optical sensors (laser interferometers, laser vibrometers), etc.

The output of the sensors SENS1, SENS2 may be connected respectively to amplifiers 3 and 4, the output of which is respectively connected to filters (F) 5, 6. The bandwidth of each filter 5 and 6 may be in the range of 300 Hz to 20000 Hz. The output of the filters 5, 6 is connected to a multiplexer 7, the output of which is connected to an analog to digital converter (ADC) 8. The output of the analog to digital converter 8 is connected to a processing unit (PU) 8 such as a microprocessor, a microcontroller, a DSP (digital signal processor), a programmable logical array (CPLD, FGPA), etc. The processing unit 9 may be connected to a RAM 9 a and to a ROM 10.

The ROM 10, or any other memory communicating with the processing unit 9, contains a database of N reference signature functions SIG_(Rj)(ω), for j=1 . . . N, corresponding to N predetermined active areas 1 a of the object 1, as will be described hereafter. Each of these active areas may correspond for instance to a particular information, and may be materialized or not by a marking or other indication on the object.

The ROM 10 may be a hard disk, but also an EPROM, or an EEPROM, or likewise. Using an EEPROM can permit to reconfigure easily the device, for example for other applications, by recording new active areas 1 a.

The reference signature functions may be for instance calculated during a learning step, e.g. before the device is used in normal use. The reference signature functions may be calculated for each single device 1-10, or these reference signature functions may be calculated only once for one device 1-10 and then used for all identical devices during normal use.

During the learning step, one generates an impact on each predetermined active area 1 a of the object 1, which is sensed by sensors SENS1, SENS2. For each impact on an active area j (j=1 . . . N), the sensors SENS1, SENS2 generate acoustic signals which are respectively amplified by amplifiers 3, 4, filtered by filters 5, 6, multiplexed by multiplexer 7 and sampled by analog to digital converter 8. Analog to digital converter 8 thus outputs two reference signals r_(1j)(t), r_(2j)(t) originating respectively from the two sensors SENS1, SENS2.

Respective Fourier transforms R_(1j)(ω), R_(2j)(ω) of the reference acoustic signals r_(1j)(t), r_(2j)(t) are then computed. The Fourier transform R_(ij)(ω) of each reference acoustic signal equals:

R _(ij)(ω)=C _(i)(ω)·H _(Rij)(ω)·E _(Rj)(ω),  (1)

where C_(i)(ω) is the Fourier transform of the impulse response of sensor i (i=1, 2), H_(Rij)(ω) is a propagation function, dependant on an acoustic wave propagation path in the object between active area j and sensor i, and E_(Rj)(ω) is the Fourier transform of the impact waveform on active area j.

Then, a reference signature function is calculated:

SIG _(Rj)(ω)=R ₁ j(ω)·R ₂ j(ω)*,  (2)

where * is the complex conjugate operator. When using equation (1) to develop equation (2), one obtains:

SIG _(Rj)(ω)=C ₁(ω)·H _(R1) j(ω)·E _(Rj)(ω)·C ₂(ω)*·H _(R2) j(ω)*·E _(Rj)(ω)*.  (3)

E_(Rj)(ω)·E_(Rj)(ω)*=|E_(Rj)(ω)|², so that equation (3) is equivalent to equation (4):

SIG _(Rj)(ω)=C ₁(ω)·C ₂(ω)*·H _(R1) j(ω)·H _(R2) j(ω)*·|E _(Rj)(ω)|²  (4)

During normal use of the device, when an impact is generated on the object 1, e.g. when a user hits or touches the object 1 with a finger or with another object (stylus, pen or else) the sensors SENS1, SENS2 receive acoustic signals. These acoustic signals are amplified by amplifiers 3 and 4, filtered by filters 5 and 6, multiplexed by multiplexer 7 and then sampled by analog to digital converter 8.

The sampled signals S_(i)(t) originating respectively from the sensors i (i=1, 2 in the present example) are then processed by processing unit 9, for instance according to a first embodiment of the method of the invention as shown in the flow chart of FIG. 2. This method may be carried out by a program ran on processing unit 9, comprising for instance calculation means S101-S103, comparison means S104-S110 and processing means S111.

In this embodiment, respective Fourier transforms S₁(ω) and S₂(ω) of the two sampled acoustic signals S₁(t) and S₂(t) are computed (preferably only for positive frequencies ω) by calculation means in steps S101 and S102. These Fourier transforms may be Fast Fourier Transforms (FFT), permitting thus to obtain quick results, without a high calculation power.

The Fourier transform S_(i)(ω) of each acoustic signal equals:

S _(i)(ω)=C _(i)(ω)·H _(Si)(ω)·E _(S)(ω)  (5)

where C_(i)(ω) is the Fourier transform of the impulse response of sensor i, H_(Si)(ω) is a propagation function, dependant on an acoustic wave propagation path in the object between the location of the impact and sensor i, and E_(S)(ω) is the Fourier transform of the impact waveform.

At step S103, the calculating means compute a sample signature function:

SIG _(S)(ω)=S ₁(ω)·S ₂(ω)*,  (6)

where * is the complex conjugate operator. When using equation (5) to develop equation (6), one obtains:

SIG _(S)(ω)=C ₁(ω)·H _(S1)(ω)·E _(S)(ω)·C ₂(ω)*·H _(S2)(ω)*·E _(S)(ω)*.  (7)

E_(S)(ω)·E_(S)(ω)*=|E_(S)(ω)|², so that:

SIG _(S)(ω)=C ₁(ω)·C ₂(ω)*·H _(S1)(ω)·H _(S2)(ω)*·|E _(S)(ω)|²  (8)

After initializing comparison means at step S104, for each predetermined area j of the object, an intermediary estimator (correlation function) is calculated at step S105:

COR _(j)(ω)=SIG _(Rj)(ω)·SIG _(S)(ω)*.  (9)

When using equations (4) and (8) to develop equation (9) one obtains equation (10):

COR _(j)(ω)=|C ₁(ω)|² ·|C ₂(ω)|² ·|E _(Rj)(ω)|² ·|E _(S)(ω)|² ·H _(R1) j(ω)·H _(R2) j(ω)*·H _(S1)(ω)*·H _(S2)(ω)  (10)

Since |C₁(ω)|², |C₂(ω)|², |E_(Rj)(ω)|² and |E_(S)(ω)|² are square moduluses whose phase equals zero, the phase φ(COR_(j)(ω)) of the intermediary estimator COR_(j)(ω) does not depend on the impulse responses C₁(ω), C₂(ω) of the sensors 3, 4 and on the impact waveforms E_(Rj)(ω), E_(S)(ω). This phase φ(COR_(j)(ω) depends only on the phase of H_(R1j)(ω)·H_(R2j)(ω)*·H_(S1)(ω)*·H_(S2)(ω), i.e. on the acoustic wave propagation paths in the object during the learning step and the.

The method of the present invention is based on the observation that:

-   -   if the impact which generated the sampled signals s₁(t), s₂(t)         was not on active area j, then the phase of COR_(j)(ω) is         variable and different from 0,     -   whereas if the impact which generated the sampled signals s₁(t),         s₂(t) was on active area j, then the phase of COR_(j)(ω) is         equal to 0, since:

COR _(j)(ω)=|C ₁(ω)|² ·|C ₂(ω)|² ·|E _(Rj)(ω)|² ·|E _(S)(ω)|² ·|H ₁ j(ω)|² ·|H ₂ j(ω)|²  (11).

Thus, it is possible to determine whether an impact on the object 1 was made on any active area 1 a, and if so, to determine on which active area.

Since the method of the invention is based on direct or indirect determination of the phase of COR_(j)(ω), it should be noted that the accuracy of this method is not altered by the use of different types of impact or by the use of sensors 3, 4 of different characteristics, because this phase is in any case independent from the impact waveforms used during the learning step and during normal use, and because this phase is also independent from the responses of the sensors SENS1, SENS2.

In steps S106 and S107, the phase φ(COR_(j)(ω)) is examined, to estimate how much SIG_(S)(ω) matches with SIG_(Rj)(ω). To this end, the comparison means may calculate a function δ_(j)(ω) in Step 106, as shown FIGS. 3A and 3B. This function δ_(j)(ω) may be calculated as follows:

-   -   if the phase φ(COR_(j)(ω)) belongs to, for example, an angular         interval I₁=[b1;a1], with a₁>0 and b₁<0, then δ_(j)(ω)=ε₁=1;     -   else, δ_(j)(ω)=ε₂=0.

It should be noted that, in step S106, it is not necessary to compute φ(COR_(j)(ω)). For instance, if b₁=−a1, the function δ_(j)(ω) may as well be calculated as follows:

-   -   if Re(COR_(j)(ω)>|Im(COR_(j)(ω))|/tan(a1), then δ_(j)(ω)=ε₁=1;     -   else, δ_(j)(ω)=ε₂=0.

In step S107, the function δ_(j)(ω) is integrated on a study frequency interval B=[ω_(min), ω_(max)] in order to obtain a similarity estimator

α_(j)=K·∫_(B)δ_(j)(ω)·dω, where K is for example a constant of normalization, which equals to (or is proportional to) the inverse of the length of the interval B: K=1/(ω_(max)−ω_(min)).

This estimator α_(j) is simple to compute, does not require a high calculation power and correctly represents the similarity of the sampled signals s₁(t), s₂(t) with the reference signals r₁(t), r₂(t).

Once the N similarity estimators α_(j) are calculated and stored in a memory, the maximal similarity estimator α_(j) ₀ is determined by comparison means in step S110. This can be carried out with a simple sequence of comparisons. In a variant, the maximum similarity estimator α_(j) ₀ can be determined in each iteration of the comparison means when computing the similarity estimators α_(j).

In order to eventually determine the active area in which an impact occurred, the greatest similarity estimator α_(j) ₀ has to be greater than a predetermined threshold of confidence VAL in step S111. For example, α_(j) ₀ has to be greater than VAL=0.5 to be recognized as valid. If α_(j) ₀ is greater than this threshold of confidence VAL, the active area j₀ is determined by processing means as the active area in which an impact occurred. Then, an information associated to this active area may be transmitted to a software, or an action can be launched by the processing means 9, etc. Else, the impact is considered as interference or as perturbation.

In a second embodiment of the invention, several angular intervals I_(i) may be used in step 106, the other steps remaining the same as in the first embodiment. For example, FIGS. 4A and 4B illustrate such a construction in the example of 4 possible values of α_(j) according to the phase φ(COR_(j)(ω)).

There, the phase φ(COR_(j)(ω)) is studied as follows:

-   -   if the phase φ(COR_(j)(ω)) belongs to the interval I₁=[b₁;a₁]         with a₁>0 and b₁<0, then, then δ_(j)(ω)=ε₁=1;     -   if the phase φ(COR_(j)(ω)) belongs to the interval         I₂=[b₂;b₁[═]a₁;a₂], with a₂>a₁ and b₂<b₁, then δ_(j)(ω)=ε₂, with         ε₂<1;     -   if the phase φ(COR_(j)(ω)) belongs to the interval         I₃=[b₃;b₂[∪]a₂;a₃], with 180°>a₃>a₂ and −180°<b₃<b₂ (preferably         with 90°>a₃>a₂ and −90°<b₃<b₂), then δ_(j)(ω)=δ₃, with ε₃<ε₂;     -   else, δ_(j)(ω)=ε₄=0.

As in the first embodiment of the invention, it should be noted that, in step S106, it is not necessary to compute φ(COR_(j)(ω)). For instance, if b₁=−a₁, b₂=−a₂, and b₃=−a₃, then the function δ_(j)(ω) may as well be calculated as follows:

if Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₁), then δ_(j)(ω)=δ₁=1;

-   -   if         |Im(COR_(j)(ω))|/tan(a₁)>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₂),         then δ_(j)(ω)=ε₂;     -   if         |Im(COR_(j)(ω))|/tan(a₂)>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₃),         then δ_(j)(ω)=ε₃;     -   else, δ_(j)(ω)=0.

Re(COR_(j)(ω) and Im(COR_(j)(ω)) are respectively the real part and the imaginary part of the complex number COR_(j)(ω).

For instance, ε₂ and ε₃ could respectively equal cos (a₁) and cos(a₂).

More generally, the phase of COR_(j)(ω) could be compared to a plurality of n angular thresholds 0<a₁<a₂< . . . <a_(n) as follows:

-   -   if Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₁), then δ_(j)(ω)=ε₁=1;     -   if         |Im(COR_(j)(ω))|/tan(a₁)>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₂),         then δ_(j)(ω)=ε₂;     -   if         |Im(COR_(j)(ω))|/tan(a₂)>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₃),         then δ_(j)(ω)=ε₃;         . . .

if |Im(COR _(j)(ω))|/tan(a _(k-1))>Re(COR _(j)(ω))≧|Im(COR _(j)(ω))|/tan(a _(k)), then δ_(j)(ω)=ε_(k);  (12)

. . .

-   -   if         |Im(COR_(j)(ω))|/tan(a_(n-2))>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a_(n−1)),         then δ_(j)(ω)=ε_(n−1);     -   else, δ_(j)(ω)=ε_(n)=0.

The values ε_(k) are such that ε₁>ε₂>>ε_(n)>0, and these values may for instance equal: ε_(k)=cos(a_(k-1)), for k=2, . . . n and ε_(n+1)=0.

In this second embodiment the other steps of the method can be identical to those described above with regards to the first embodiment.

In a third embodiment of the invention, as illustrated for instance in FIG. 5, the calculation of the above correlation function COR_(j)(ω) (j=1, . . . N) is avoided.

As a matter of fact, SIG_(Rj)(ω)=A_(j)(ω)+jB_(j)(ω) (A_(j) and B_(j) are respectively the real and imaginary parts of SIG_(Rj)), and SIG_(S)(ω)*=C(ω)+jD(ω) (C and D are respectively the real and imaginary parts of SIG_(S)), so that the above equation (12) can be written as follows:

|B _(j)(ω)C(ω)+A _(j)(ω)D(ω)|/tan(a _(k-1))>A _(j)(ω)C(ω)−B _(j)(ω)D(ω)>|B _(j)(ω)C(ω)+A _(j)(ω)D(ω)|/tan(a _(k))  (13)

|B _(j)(ω)|·|C(ω)|·|+{A _(j)(ω)/B _(j)(ω)}·{(D(ω)/C(ω)}|/tan(a _(k-1))>A _(j)(ω)C(ω)−B _(j)(ω)D(ω)>|B _(j)(ω)|·|C(ω)|·|+{A _(j)(ω)/B _(j)(ω)}·{(D(ω)/C(ω)}|/tan(a _(k))  (14)

β_(j)(ω)/tan(a _(k-1))>γ_(j)(ω)>β_(j)(ω)/tan(a _(k))  (15)

wherein: β_(j)(ω)=|+{A_(j)(ω)/B_(j)(ω)}·{(D(ω)/C(ω)}| γ_(j)(ω)=signB_(j)(ω)·signC(ω)·[{A_(j)(ω)/B_(j)(ω)}−{D(ω)/C(ω)}]; signB_(j)(ω)=1 if B_(j)(ω) is positive and =−1 if B_(j)(ω) is negative; signC(ω)=1 if C(ω) is positive and =−1 if C(ω) is negative.

Therefore, this third embodiment, instead of calculating the correlation functions COR_(j)(ω), the above functions β_(j)(ω) and γ_(j)(ω) are calculated in step S105. It should be noted that this calculation is particularly simple, and only requires:

-   -   that signB_(j)(ω) and the ratio A_(j)(ω)/B_(j)(ω) be stored in         advance in memory 10 for j=1, N (i.e. one real number+1 bit,         whereas the complete calculation of the COR_(j)(ω) implied to         store the complete reference signature functions (a complex         number, i.e. the equivalent of two real numbers);     -   that signC(ω) and the ratio D(ω)/C(ω) be stored at the beginning         of step S105, after which only a very limited number of         operations remain to be done at step S105 to calculate β_(j)(ω)         and γ_(j)(ω).

Then, at step S106, the phase of COR_(j)(ω) is compared to n−1 angular thresholds 0<a₁<a₂< . . . <a_(n−1) through equation (15) as follows:

-   -   if γ_(j)(ω)≧β_(j)(ω)/tan(a₁), then δ_(j)(ω)=ε₁=1;         . . .     -   if n is greater than 2 and         β_(j)(ω)/tan(a_(k-1))>γ_(j)(ω)≧β_(j)(ω)/tan(a_(k)), then         δ_(j)(ω)=ε_(k), for k=2, . . . n−1;     -   else, δ_(j)(ω)=ε_(n)=0.

The values ε_(k) are such that ε₁>ε₂> . . . >ε_(n)>0, and these values may for instance equal: ε_(k)=cos(a_(k-1)), for k=2, . . . n.

If n=1, this comparison is limited to:

-   -   if γ_(j)(ω)≧β_(j)(ω)/tan(a₁), then δ_(j)(ω)=1;     -   else, δ_(j)(ω)=0.

The subsequent steps S107-S111 of the method may be identical to the steps explained above for the first and second embodiments of the invention.

According to one further embodiment of the invention, the sampling of the acoustic signals may be triggered only if the signals received by the analog to digital converter 8 are greater than a trigger threshold. Consequently, the device only samples relevant acoustic signals. This permits to reduce the interference sensibility. In this embodiment, the sampled signals S₁(t) and S₂(t) may be delayed compared to the real signals. As a matter of fact, to avoid that the trigger threshold prevents the record of the very beginning of acoustic signals, a delay device may be added, in order to record the waveform of the signal a few microseconds before the sampling step is triggered. 

1. A method for determining the position of impacts on an object, said object comprising: two acoustic sensors (SENS1, SENS2); N predetermined active areas, whereby N is an integer at least equal to 1; said method comprising the steps of: (a) receiving two acoustic signals S₁(t) and S₂(t) originating respectively from said acoustic sensors (SENS1, SENS2) and generated by an impact received on said object; (b) calculating a sample signature function: SIG _(S)(ω)=S ₁(ω)·S ₂(ω)*, where S₁(ω) and S₂(ω) are the respective Fourier transforms of S₁(t) and S₂(t), and where * is the complex conjugate operator; (c) comparing SIG_(S)(ω) with N predetermined reference signature functions SIG_(Rj)(ω) each corresponding to a predetermined active area j, for j from 1 to N; (d) determining an active area (1 a) in which the impact occurred, on the basis of the comparison of step (c).
 2. The method as claimed in claim 1, wherein each reference signature function equals: SIG _(R) _(j) (ω)=R ₁ j(ω)·R ₂ j(ω)* where R_(1j)(ω) and R_(2j)(ω) are Fourier transforms of acoustic signals r_(1j)(t) and r_(2j)(t) received by each of the respective acoustic sensors when an impact occurs on the predetermined area j.
 3. The method as claimed in claim 1, wherein step (c) comprises the calculation of a similarity estimator α_(j) representing a function of the phase φ(COR_(j)(ω)) of COR_(j)(ω)=SIG_(R) _(j) (ω)·SIG_(S)(ω)*.
 4. The method as claimed in claim 3, wherein step (c) comprises the calculation of a function δ_(j)(ω) for j from 1 to N, wherein δ_(j)(ω)=ε_(k), if φ(COR_(j)(ω)) belongs to I_(k), where ε_(k) is a predetermined value and I_(k) a corresponding angular interval for k from 1 to n, where n is an integer greater than
 1. 5. The method as claimed in claim 4, wherein the values ε_(i) are not greater than
 1. 6. The method as claimed in claim 4, wherein: if |φ(COR_(j)(ω))|≦a1, then δ_(j)(ω)=ε₁, . . . if n is greater than 2 and a_(k-1)<|φ(COR_(j)(ω))|≦a_(k), then δ_(j)(ω)=ε_(k), for k=2 . . . n−1, . . . if |φ(COR_(j)(ω))|>a_(n−1), then δ_(j)(ω)=ε_(n), wherein a_(k) is increasing with k and ε_(k) is decreasing with k.
 7. The method as claimed in claim 6, wherein: if Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₁), then δ_(j)(ω)=δ₁, . . . if n is greater than 2 and |Im(COR_(j)(ω)|/tan(a_(k-1))>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a_(k)) then δ_(j)(ω)=ε_(k), for k=2 . . . n−1, . . . else, δ_(j)(ω)=ε_(n), and wherein Re(COR_(j)(ω)) is the real part of COR_(j)(ω) and Im(COR_(j)(ω)) is the imaginary part of COR_(j)(ω).
 8. The method according to claim 6, wherein: if γ_(j)(ω)≧β_(j)(ω)/tan(a₁), then δ_(j)(ω)=ε₁=1; . . . if n is greater than 2 and β_(j)(ω)/tan(a_(k-1))>γ_(j)(ω)≧β_(j)(ω)/tan(a_(k)), then δ_(j)(ω)=ε_(k), for k=2, . . . n−1; . . . else, δ_(j)(ω)=ε_(n), and wherein: β_(j)(ω)=|1+{A_(j)(ω)/B_(j)(ω)}·{(D(ω)/C(ω)}|, γ_(j)(ω)=signB_(j)(ω)·signC(ω)·[{A_(j)(ω)/B_(j)(ω)}−{D(ω)/C(ω)}], signB_(j)(ω)=1 if B_(j)(ω) is positive and =−1 if B_(j)(ω) is negative, signC(ω)=1 if C(ω) is positive and =−1 if C(ω) is negative, A_(j)(ω) and B_(j)(ω) are respectively the real part and the imaginary part of each reference signature function SIG_(Rj)(ω), C(ω) and D(ω) are respectively the real part and the imaginary part of the complex conjugate sample signature function SIG_(S)(ω)*.
 9. The method as claimed in claim 6, wherein ε₁=1 and ε_(n)=0.
 10. The method as claimed in claim 9, wherein n is greater than 2 and ε_(k)=cos(a_(k-1)), for k=2, . . . n−1.
 11. The method as claimed in claim 4, wherein α_(j) =K·∫ _(B)δ_(j)(ω)·dω, where B is a frequency interval and K a constant.
 12. The method as claimed in claim 11, wherein B=[ω_(min)ω_(max)] and K is proportional to 1/(ω_(max)−ω_(min)).
 13. The method as claimed in claim 3, wherein the active area j₀ in which the impact occurred is determined such that α_(j) ₀ is the greatest similarity estimator among the N calculated similarity estimators α_(j).
 14. The method as claimed in claim 13, wherein it is concluded that the impact occurred in the area j₀ only if α_(j) ₀ is considered as valid in step (d).
 15. The method of claim 14, wherein α_(j) ₀ is considered as valid if α_(j) ₀ is greater than a predetermined threshold of confidence (VAL).
 16. The method as claimed in claim 14, wherein it is concluded that there is no impact if α_(j) ₀ is not considered as valid in step (d).
 17. The method as claimed in claim 1, wherein step (a) begins if the acoustic signals S₁(t) and S₂(t) are above a predetermined trigger threshold.
 18. The method as claimed in claim 1, wherein the acoustic signals S₁(t) and S₂(t) in step (a) are delayed relative to real audio signals.
 19. The method as claimed in claim 1, wherein the Fourier transform is a Fast Fourier transform.
 20. A device for determining the position of impacts on an object, comprising: two acoustic sensors adapted to be borne by said object for receiving acoustic signals S₁(t) and S₂(t) generated by an impact on said object; memory means (10) comprising N reference signature functions, corresponding to N predetermined active areas of said object, whereby N is an integer at least equal to 1; calculation means (S101-S103) for calculating a sample signature function SIG _(S)(ω)=S ₁(ω)·S ₂(ω)*, where S₁(ω) and S₂(ω) are the respective Fourier transforms of S₁(t) and S₂(t), and where * is the complex conjugate operator; comparison means (S104-S110) for comparing SIG_(S)(ω) with N predetermined reference signature functions SIG_(R) _(j) (ω) for j from 1 to N; processing means (S111) for determining an active area (1 a) in which the impact occurred, on the basis of results given by said the comparison means.
 21. The device as claimed in claim 20, wherein each reference signature function equals: SIG _(R) _(j) (ω)=R ₁ j(ω)·R ₂ j(ω)* where R_(1j)(ω) and R_(2j)(ω) are Fourier transforms of acoustic signals r_(1j)(t) and r_(2j)(t) received by each of the respective acoustic sensors when an impact occurs on the predetermined area j.
 22. The method as claimed in claim 1, wherein said comparison means (S104-S110) are adapted to calculate a similarity estimator α_(j) representing a function of the phase φ(COR_(j)(ω)) of COR_(j)(ω)=SIG_(R) _(j) (ω)·SIG_(S)(ω)*.
 23. The device as claimed in claim 22, wherein said comparison means (S104-S110) are adapted to calculate a function δ_(j)(ω) for j from 1 to N, wherein δ_(j)(ω)=ε_(k), if φ(COR_(j)(ω)) belongs to I_(k), where ε_(k) is a predetermined value and I_(k) a corresponding angular interval for k from 1 to n, where n is an integer greater than
 1. 24. The device as claimed in claim 23, wherein the values ε_(i) are not greater than
 1. 25. The device as claimed in claim 23, wherein said comparison means (S104-S110) are adapted so that: if |φ(COR_(j)(ω))|≦a1, then δ_(j)(ω)=ε₁, . . . if n is greater than 2 and a_(k-1)<|φ(COR_(j)(ω)|≦a_(k), then δ_(j)(ω)=ε_(k), for k=2 . . . n−1, . . . if |φ(COR_(j)(ω))|>a_(n−1), then δ_(j)(ω)=ε_(n), wherein a_(k) is increasing with k and ε_(k) is decreasing with k.
 26. The device as claimed in claim 25, wherein said comparison means (S104-S110) are adapted so that: if Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a₁), then δ_(j)(ω)=ε₁, . . . if n is greater than 2 and |Im(COR_(j)(ω))|/tan(a_(k-1))>Re(COR_(j)(ω))≧|Im(COR_(j)(ω))|/tan(a_(k)), then δ_(j)(ω)=ε_(k), for k=2 . . . n−1, . . . else, δ_(j)(ω)=ε_(n), and wherein Re(COR_(j)(ω)) is the real part of COR_(j)(ω) and Im(COR_(j)(ω)) is the imaginary part of COR_(j)(ω).
 27. The device according to claim 25, wherein said comparison means (S104-S110) are adapted so that: if γ_(j)(ω)≧β_(j)(ω)/tan(a₁), then δ_(j)(ω)=ε₁=1; . . . if n is greater than 2 and β_(j)(ω)/tan(a_(k-1))>γ_(j)(ω)≧β_(j)(ω)/tan(a_(k)), then δ_(j)(ω)=ε_(k), for k=2, . . . n−1; . . . else, δ_(j)(ω)=ε_(n), and wherein: β_(j)(ω)=|1+{A_(j)(ω)/B_(j)(ω)}·{(D(ω)/C(ω)}|, γ_(j)(ω)=signB_(j)(ω)·signC(ω)·[{A_(j)(ω)/B_(j)(ω)}−{D(ω)/C(ω)}], signB_(j)(ω)=1 if B_(j)(ω) is positive and =−1 if B_(j)(ω) is negative, signC(ω)=1 if C(ω) is positive and =−1 if C(ω) is negative, A_(j)(ω) and B_(j)(ω) are respectively the real part and the imaginary part of each reference signature function SIG_(Rj)(ω), C(ω) and D(ω) are respectively the real part and the imaginary part of the complex conjugate sample signature function SIG_(S)(ω)*.
 28. The device as claimed in claim 25, wherein ε₁=1 and ε_(n)=0.
 29. The device as claimed in claim 28, wherein n is greater than 2 and ε_(k)=cos(a_(k-1)), for k=2, . . . n−1.
 30. The device as claimed in claim 23, wherein said comparison means (S104-S110) are adapted so that: α_(j) =K·∫ _(B)δ_(j)(ω)·dω, where B is a frequency interval and K a constant.
 31. The device as claimed in claim 22, wherein the processing means (S111) are adapted to determine the active area j₀ in which the impact occurred such that α_(j) ₀ is the greatest similarity estimator among the N calculated similarity estimators α_(j).
 32. The device as claimed in claim 31, wherein the processing means (S111) are adapted to determine that the impact occurred in the area j₀ only if α_(j) ₀ is considered as valid.
 33. The device of claim 32, wherein the processing means (S111) are adapted to determine that α_(j) ₀ is valid if α_(j) ₀ is greater than a predetermined threshold of confidence (VAL).
 34. The device as claimed in claim 32, wherein the processing means (S111) are adapted to determine that there is no impact if α_(j) ₀ is not considered as valid. 